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Annual Review of Earth and Planetary Sciences

Volume 47, 2019

Unanticipated Uses of the Global Positioning System

Abstract

Global Positioning System (GPS) instruments are routinely used today to measure crustal deformation signals from tectonic plate motions, faulting, and glacial isostatic adjustment. In parallel with the expansion of GPS networks around the world, several new and unexpected applications of GPS have been developed. For example, GPS instruments are now being used routinely to measure ground motions during large earthquakes. Access to real-time GPS data streams has led to the development of better hazard warnings for tsunamis, flash floods, earthquakes, and volcanic eruptions. Terrestrial water storage changes can be derived from GPS vertical coordinate time series. Finally, GPS signals that reflect on the surfaces below a GPS antenna can be used to measure soil moisture, snow accumulation, vegetation water content, and water levels. In the future, combining GPS with the signals from the Russian, European, and Chinese navigation constellations will significantly enhance these applications.

  • ▪  GPS data are now routinely used to study the dynamics of earthquake rupture.
  • ▪  GPS instruments are an integral part of warning systems for earth- quakes, tsunamis, flash floods, and volcanic eruptions.
  • ▪  Reflected GPS signals provide a new source of soil moisture, snow depth, vegetation water content, and tide gauge data.
  • ▪  GPS networks can sense changes in soil moisture, groundwater, and snow depth and thus can contribute to water resource assessments.

Keyword(s): cryosphere, GPS, hazards, hydrology, seismology, tides
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2019-05-30
2025-06-13
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Literature Cited

  1. Agnew DC, Larson KM 2007. Finding the repeat times of the GPS constellation. GPS Solut 11:171–76
     [Google Scholar]
  2. Allen RM, Melgar D 2019. Earthquake early warning: a review of advances, scientific challenges, and societal needs. Annu. Rev. Earth Planet. Sci. 47: In press
    [Google Scholar]
  3. Altamimi Z, Rebischung P, Métivier L, Collilieux X 2016. ITRF2014: a new release of the International Terrestrial Reference Frame modeling nonlinear station motions. J. Geophys. Res. Solid Earth 121:6109–31
     [Google Scholar]
  4. Anthes RA, Bernhardt PA, Chen Y, Cucurull L, Dymond KF et al. 2008. The COSMIC/FORMOSAT-3 mission: early results. Bull. Am. Meteorol. Soc. 89:3313–33
     [Google Scholar]
  5. Aranzulla M, Cannavo F, Scollo S 2014. Detection of volcanic plumes by GPS: the 23 November 2013 episode on Mt. Etna. Ann. Geophys. 57: https://doi.org/10.4401/ag-6622
    [Crossref] [Google Scholar]
  6. Argus DF, Fu Y, Landerer FW 2014. Seasonal variation in total water storage in California inferred from GPS observations of vertical land motion. Geophys. Res. Lett. 41:1971–80
     [Google Scholar]
  7. Argus DF, Landerer FW, Wiese DN, Martens HR, Fu Y et al. 2017. Sustained water loss in California's mountain ranges during severe drought from 2012 to 2015 inferred from GPS. J. Geophys. Res. Solid Earth 122:10559–85
     [Google Scholar]
  8. Artru J, Ducic V, Kanamori H, Lognonné P, Murakami M 2005. Ionospheric detection of gravity waves induced by tsunamis. Geophys. J. Int. 160:840–48
     [Google Scholar]
  9. Avallone A, Marzario M, Cirella A, Piatanesi A, Rovelli A et al. 2011. Very high rate (10 Hz) GPS seismology for moderate‐magnitude earthquakes: the case of the Mw 6.3 L'Aquila (central Italy) event. J. Geophys. Res. 116:B02305
     [Google Scholar]
  10. Axelrad P, Comp CC, MacDoran P 1996. SNR-based multipath error correction for GPS differential phase. IEEE Trans. Aerosp. Electron. Syst. 32:650–60
     [Google Scholar]
  11. Bar-Sever YE, Kroger PM, Borjesson JA 1998. Estimating horizontal gradients of tropospheric path delay with a single GPS receiver. J. Geophys. Res. 103:B35019–35
     [Google Scholar]
  12. Bevis M, Businger S, Herring TA, Rocken C, Anthes RA, Ware RH 1992. GPS meteorology: remote sensing of atmospheric water vapor using the Global Positioning System. J. Geophys. Res. 97:D1415787–801
     [Google Scholar]
  13. Blewitt G, Kreemer C, Hammond WC, Plag HP, Stein S, Okal E 2006. Rapid determination of earthquake magnitude using GPS for tsunami warning systems. Geophys. Res. Lett. 33:L11309
     [Google Scholar]
  14. Bock Y, Melgar D 2016. Physical applications of GPS geodesy: a review. Rep. Prog. Phys. 79:10106801
     [Google Scholar]
  15. Bock Y, Prawirodirdjo L, Melbourne TI 2004. Detection of arbitrarily large dynamic ground motions with a dense high-rate GPS network. Geophys. Res. Lett. 31:L06604
     [Google Scholar]
  16. Boehm J, Niell A, Tregoning P, Schuh H 2006. Global mapping function (GMF): a new empirical mapping function based on numerical weather model data. Geophys. Res. Lett. 33:L07304
     [Google Scholar]
  17. Borsa AA, Agnew DC, Cayan DR 2014. Ongoing drought-induced uplift in the western United States. Science 345:1587–90
     [Google Scholar]
  18. Borsa AA, Mencin D, van Dam TM 2017. The weight of a storm: what observations of Earth surface deformation can tell us about Hurricane Harvey Abstract NH23E-2872 presented at the American Geophysical Union Meeting New Orleans, LA: Dec 11–15
     [Google Scholar]
  19. Chen F, Crow WT, Bindlish R, Colliander A, Burgin MS et al. 2018. Global-scale evaluation of SMAP, SMOS and ASCAT soil moisture products using triple collocation. Remote Sens. Environ. 214:1–13
     [Google Scholar]
  20. Chew CC, Small EE 2018. Soil moisture sensing using spaceborne GNSS reflections: comparison of CYGNSS reflectivity to SMAP soil moisture. Geophys. Res. Lett. 45:4049–57
     [Google Scholar]
  21. Choi K, Bilich A, Larson KM, Axelrad P 2004. Modified sidereal filtering: implications for high-rate GPS positioning. Geophys. Res. Lett. 31:L22608
     [Google Scholar]
  22. Delouis B, Nocquet JM, Vallee M 2010. Slip distribution of the February 27, 2010 Mw = 8.8 Maule earthquake, central Chile, from static and high-rate GPS, InSAR, and broadband teleseismic data. Geophys. Res. Lett. 37:L17305
     [Google Scholar]
  23. Dong D, Fang P, Bock Y, Cheng MK, Miyazaki S 2002. Anatomy of apparent seasonal variations from GPS-derived site position time series. J. Geophys. Res. 107:B42075
     [Google Scholar]
  24. Dow JM, Neilan RE, Rizos C 2009. The international GNSS service in a changing landscape of global navigation satellite systems. J. Geodesy 83:191–98
     [Google Scholar]
  25. Elósegui P, Davis JL, Jaldehag R, Johansson J, Niell A, Shapiro I 1995. Geodesy using the global positioning system: the effects of signal scattering on estimates of site position. J. Geophys. Res. 100:B79921–34
     [Google Scholar]
  26. Elósegui P, Davis JL, Oberlander D, Baena R, Ekstrom G 2006. Accuracy of high-rate GPS for seismology. Geophys. Res. Lett. 33:L11308
     [Google Scholar]
  27. Fournier N, Jolly AD 2014. Detecting complex eruption sequence and directionality from high-rate geodetic observations: the August 6, 2012 Te Maari eruption, Tongariro, New Zealand. J. Volcanol. Geotherm. Res. 286:387–96
     [Google Scholar]
  28. Fu Y, Freymueller JT, Jensen T 2012. Seasonal hydrological loading in southern Alaska observed with GPS and GRACE. Geophys. Res. Lett. 39:1515310
     [Google Scholar]
  29. Galetzka J, Melgar D, Genrich JG, Geng J, Owen S et al. 2015. Slip pulse and resonance of the Kathmandu basin during the Gorkha earthquake, Nepal. Science 349:1091–95
     [Google Scholar]
  30. Ge L, Han S, Rizos C, Ishikawa Y, Hoshiba M et al. 2000. GPS seismometers with up to 20-Hz sampling rate. Earth Planets Space 52:881–84
     [Google Scholar]
  31. Genrich JF, Bock Y 1992. Rapid resolution of crustal motion at short ranges with the Global Positioning System. J. Geophys. Res. 97:B33261–69
     [Google Scholar]
  32. Georgiadou Y, Kleusberg A 1988. On carrier signal multipath effects in relative GPS positioning. Manuscr. Geod. 13:172–79
     [Google Scholar]
  33. Gomberg J, Bodin P, Larson KM, Dragert H 2004. Earthquakes nucleated by transient deformations caused by the M = 7.9 Denali, Alaska, earthquake. Nature 427:621–24
     [Google Scholar]
  34. Grapenthin R, Freymueller JT, Kaufman AM 2013. Geodetic observations during the 2009 eruption of Redoubt Volcano, Alaska. J. Volcanol. Geotherm. Res. 259:115–32
     [Google Scholar]
  35. Griffiths J, Ray JR 2009. On the precision and accuracy of IGS orbits. J. Geodesy 83:277–87
     [Google Scholar]
  36. Heki K 2001. Seasonal modulation of interseismic strain buildup in northeastern Japan driven by snow loads. Science 293:89–92
     [Google Scholar]
  37. Hernandez-Pajares M, Juan JM, Sanz J, Orus R 2007. Second-order ionospheric term in GPS: implementation and impact on geodetic estimates. J. Geophys. Res. 112:B08417
     [Google Scholar]
  38. Herring TA, Melbourne TI, Murray MH, Floyd MA, Szeliga WM et al. 2016. Plate Boundary Observatory and related networks: GPS data analysis methods and geodetic products. Rev. Geophys. 54:759–808
     [Google Scholar]
  39. Hirahara K, Nakano T, Hoso T, Matsuo S, Obana K 1994. An experiment for GPS strain seismometer. Proceedings of the Japanese Symposium on GPS December 15–16 Tokyo, Japan:67–75
     [Google Scholar]
  40. Houlié N, Briole P, Nercessian A, Murakami M 2005. Sounding the plume of the 18 August 2000 eruption of Miyakejima volcano (Japan) using GPS. Geophys. Res. Lett. 32:L05302
     [Google Scholar]
  41. Hreinsdóttir S, Sigmundsson F, Roberts MJ, Bjornsson H, Grapenthin R et al. 2014. Volcanic plume height correlated with magma pressure change at Grimsvöttn Volcano, Iceland. Nat. Geosci. 7:214–18
     [Google Scholar]
  42. Ji C, Larson KM, Tan Y, Hudnut K, Choi K 2004. Slip history of the 2003 San Simeon earthquake constrained by combining 1-Hz GPS, strong motion, and teleseismic data. Geophys. Res. Lett. 31:L17608
     [Google Scholar]
  43. Kerr RA 2005. Failure to gauge the quake crippled the warning effort. Science 307:201
     [Google Scholar]
  44. Larson KM 2013. A new way to detect volcanic plumes. Geophys. Res. Lett. 40:2657–60
     [Google Scholar]
  45. Larson KM 2016. GPS interferometric reflectometry: applications to surface soil moisture, snow depth, and vegetation water content in the western United States. WIREs Water 3:775–87
     [Google Scholar]
  46. Larson KM, Bodin P, Gomberg J 2003. Using 1 Hz GPS data to measure deformations caused by the Denali Fault earthquake. Science 300:1421–24
     [Google Scholar]
  47. Larson KM, Gutmann E, Zavorotny VU, Braun JJ, Williams M, Nievinski FG 2009. Can we measure snow depth with GPS receivers. ? Geophys. Res. Lett. 36:L17502
     [Google Scholar]
  48. Larson KM, Löfgren JS, Haas R 2013a. Coastal sea level measurements using a single geodetic GPS receiver. Adv. Space Res. 51:81301–10
     [Google Scholar]
  49. Larson KM, Ray RD, Nievinski FG, Freymueller JT 2013b. The accidental tide gauge: a GPS reflections case study from Kachemak Bay, Alaska. IEEE Geosci. Remote Sens. Lett. 10:51200–4
     [Google Scholar]
  50. Larson KM, Ray RD, Williams SDP 2017. A ten-year comparison of water levels measured with a geodetic GPS receiver versus a conventional tide gauge. J. Atmos. Ocean Technol. 34:295–307
     [Google Scholar]
  51. Larson KM, Small EE, Gutmann E, Bilich A, Braun JJ, Zavorotny VU 2008. Use of GPS receivers as a soil moisture network for water cycle studies. Geophys. Res. Lett. 35:L24405
     [Google Scholar]
  52. Larson KM, Wahr J, Munneke PK 2015. Constraints on snow accumulation and firn density in Greenland using GPS receivers. J. Glaciol. 61:101–15
     [Google Scholar]
  53. Li X, Dick G, Ge M, Heise S, Wickert J et al. 2014. Real-time GPS sensing of atmospheric water vapor: precise point positioning with orbit, clock, and phase delay corrections. Geophys. Res. Lett. 41:3615–21
     [Google Scholar]
  54. McCreight JL, Small EE, Larson KM 2014. Snow depth, density, and SWE estimates derived from GPS reflection data: validation in the western U.S. Water Resour. Res. 50:86892–909
     [Google Scholar]
  55. Miyazaki S, Larson KM 2008. Coseismic and early postseismic slip for the 2003 Tokachi-Oki earthquake sequence inferred from GPS data. Geophys. Res. Lett. 35:L04302
     [Google Scholar]
  56. Miyazaki S, Larson KM, Choi I, Hikima K, Koketsu K et al. 2004a. Modeling the rupture process of the 2003 Tokachi-Oki (Hokkaido) earthquake using 1-Hz GPS data. Geophys. Res. Lett. 31:L21603
     [Google Scholar]
  57. Miyazaki S, Segall P, Fukuda J, Kato T 2004b. Space time distribution of afterslip following the 2003 Tokachi-Oki earthquake: implications for variations in fault zone frictional properties. Geophys. Res. Lett. 31:L06623
     [Google Scholar]
  58. Moore AW, Small IJ, Gutman SI, Bock Y, Dumas JL et al. 2015. National Weather Service forecasters use precipitable water vapor for enhanced situational awareness during the Southern California summer monsoon. Bull. Am. Meteorol. Soc. 96:111867–77
     [Google Scholar]
  59. Nievinski FG, Larson KM 2014. Inverse modeling of GPS multipath for snow depth estimation, part II: application and validation. IEEE Trans. Geosci. Remote Sens. 52:106564–73
     [Google Scholar]
  60. Ohta Y, Iguchi M 2015. Advective diffusion of volcanic plume capture by dense GNSS network around Sakurajima volcano: a case study of the vulcanian eruption on July 24, 2012. Earth Planets Space 67:157
     [Google Scholar]
  61. Ozawa S, Kaidzu M, Murakami M, Imakiire T, Hatanaka Y 2004. Coseismic and postseismic crustal deformation after the Mw 8 Tokachi-Oki earthquake in Japan. Earth Planets Space 56:675–80
     [Google Scholar]
  62. Ruf C, Unwin M, Dickson J, Rose R, Rose D, Vincent M, Lyons A 2013. CYGNSS: enabling the future of hurricane prediction. IEEE Geosci. Remote Sens. Mag. 1:52–67
     [Google Scholar]
  63. Sagiya T 2004. The first decade of GEONET: 1994–2003—the continuous GPS observation in Japan and its impact on earthquake studies. Earth Planets Space 56:8xxix–xli
     [Google Scholar]
  64. Savastano G, Komjathy A, Verkhoglyadova O, Mazzoni A, Crespi M et al. 2017. Real-time detection of tsunami ionospheric disturbances with a stand-alone GNSS receiver: a preliminary feasibility demonstration. Sci. Rep. 7:46607
     [Google Scholar]
  65. Schöne T, Schön N, Thaller D 2009. IGS Tide Gauge Benchmark Monitoring Pilot Project (TIGA): scientific benefits. J. Geodesy 83:3–4249–61
     [Google Scholar]
  66. Segall P, Davis JL 1997. GPS applications for geodynamics and earthquake studies. Annu. Rev. Earth Planet. Sci. 25:301–36
     [Google Scholar]
  67. Shean DE, Christiansen K, Larson KM, Ligtenberg SRM, Joughin IR et al. 2017. GPS-derived estimates of surface mass balance and ocean-induced basal melt for Pine Island Glacier ice shelf, Antarctica. Cryosphere 11:2655–74
     [Google Scholar]
  68. Siegfried MR, Medley B, Larson KM, Fricker HA, Tulaczyk S 2017. Snow accumulation variability on a West Antarctic ice sheet observed with GPS reflectometry, 2007–2017. Geophys. Res. Lett. 44:7808–16
     [Google Scholar]
  69. Small EE, Larson KM, Braun JJ 2010. Sensing vegetation growth with GPS reflections. Geophys. Res. Lett. 37:L12401
     [Google Scholar]
  70. Small EE, Larson KM, Chew CC, Dong J, Oschner TE 2016. Validation of GPS-IR soil moisture retrievals: comparison of algorithms with different adjustments for vegetation effects. IEEE J. Sel. Top. Appl. Earth Sci. 9:104759–70
     [Google Scholar]
  71. Small EE, Roesler CJ, Larson KM 2018. Vegetation response to the 2012–2014 California drought from GPS and optical measurements. Remote Sens 10:4630–45
     [Google Scholar]
  72. Sobolev SV, Babeyko AY, Wang R, Hoechner A, Galas R et al. 2007. Tsunami early warning using GPS-shield arrays. J. Geophys. Res. 112:B08415
     [Google Scholar]
  73. Strandberg J, Hobiger T, Haas R 2016. Improving GNSS-R sea level determination through inverse modeling of SNR data. Radio Sci 51:1286–96
     [Google Scholar]
  74. van Dam T, Wahr J, Milley C, Shmakin A, Blewitt G et al. 2001. Crustal displacements due to continental water loading. Geophys. Res. Lett. 28:651–54
     [Google Scholar]
  75. Vigny C, Socquet A, Peyrat S, Ruegg JC, Metois M et al. 2011. The 2010 Mw 8.8 Maule megathrust earthquake of Central Chile, monitored by GPS. Science 332:1417–21
     [Google Scholar]
  76. Wang J, Zhang L 2007. Systematic errors in global radiosonde precipitable water vapor from comparisons with ground-based GPS measurements. J. Clim. 21:2218–37
     [Google Scholar]
  77. Williams SDP, Nievinski FG 2017. Tropospheric delays in ground-based GNSS multipath reflectometry—experimental evidence from coastal sites. J. Geophys. Res. Solid Earth 122:2310–27
     [Google Scholar]
  78. Yue H, Lay T 2011. Inversion of high‐rate (1 sps) GPS data for rupture process of the 11 March 2011 Tohoku earthquake (Mw 9.1). Geophys. Res. Lett. 38:L006G09
     [Google Scholar]
  79. Zou R, Wang Q, Freymueller JT, Poutanen M, Cao X 2015. Seasonal hydrological loading in Southern Tibet detected by joint analysis of GPS and GRACE. Sensors 15:30525–38
     [Google Scholar]
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Unanticipated Uses of the Global Positioning System
Annual Review of Earth and Planetary Sciences 47, 19 (2019); https://doi.org/10.1146/annurev-earth-053018-060203
/content/journals/10.1146/annurev-earth-053018-060203
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